An introduction to optimal design of experiments

Design of experiments or DOE is a key tool for researchers. However, experimenters often have to deal with a mismatch between standard experimental designs, such as factorial and fractional factorial designs and central composite designs, and the features of their problems. This introductory talk motivates the standard and routine use of a fully flexible approach to design of experiments, named optimal design of experiments. The increasing computing power and the availability of user-friendly software for the tailor-made design of experiments has made optimal experimental design a key tool for researchers in any field of study.

Professor Dr. Peter Goos, KU Leuven, BIOSYST-MeBioS (BE) Professor of Statistics peter.goos@kuleuven.be

Peter Goos is a full professor at the Faculty of Bio-Science Engineering of KU Leuven, and at the Faculty of Business and Economics of the University of Antwerp, where he teaches various introductory and advanced courses on statistics and probability. His main research area is the statistical design and analysis of experiments. Besides numerous influential articles in various kinds of scientific journals, he published the books The Optimal Design of Blocked and Split-Plot Experiments, Optimal Experimental Design: A Case Study Approach, Statistics with JMP: Graphs, Descriptive Statistics and Probability and Statistics with JMP: Hypothesis Tests, ANOVA and Regression. For his work, Peter has received four Shewell Awards, two Lloyd S. Nelson Awards, the Youden Award and a Brumbaugh Award from the American Society for Quality, the Ziegel Award and the Statistics in Chemistry Award from the American Statistical Association, and the Young Statistician Award of the European Network for Business and Industrial Statistics (ENBIS). Peter is also cofounder of EFFEX™ which provides software for design of experiments and the analysis of experimental data.

Information: tel. 25 002307

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